Demands for higher data rates for mobile services are steadily increasing. At the same time modern mobile communication systems as 3rd generation systems (3G as abbreviation) and 4th generation systems (4G as abbreviation) provide enhanced technologies which enable higher spectral efficiencies and allow for higher data rates and cell capacities. As the demand for high-rate services grows faster than the cell capacities, operators are urged to increase the number of cells in their networks, i.e. the density of base stations increases. Base station transceivers are major contributors to the overall power consumption of a mobile communication network and therewith also major contributors to the operational expenditures (OPEX as abbreviation) operators are facing. One power saving strategy is to move processing capacity away from the base station transceivers and towards centralized processing units providing processing capabilities for several base station transceivers. The processing equipment of a base station transceiver consumes a significant part of a base station transceiver's total power, although the processing capabilities of a base station transceiver are only fully exploited in high load conditions, which do not occur permanently, but rather during peak hours only.
Currently, the radio access of mobile networks (RAN as abbreviation for Radio Access Network) uses base stations or base station transceivers, as e.g. eNodeBs for the most recent technology LTE (as abbreviation for Long Term Evolution), handling all radio, baseband and control functions. These base stations consist of voluminous antennas at elevated positions with electronic systems requiring considerable spatial installation volume. In addition, supplementary systems for power supply, air conditioning, etc. are to be installed in close proximity. In densely populated areas such installations are to be repeated over a grid of ˜1 km or less mesh width.
Much of the entire RAN's CAPEX (as abbreviation for Capital Expenditure) and OPEX is therefore attributed to each site's individual processing units, as for example site rent, infrastructure, processing hardware, maintenance, etc. Several approaches to cut at least a big share of these cost elements have been subject to recent research activities. Some solutions reduce emitted power and processing complexity and therewith reduce required volume, however, these solutions are at the expense of increasing the number of required sites.